Various brands and configurations of weather radar systems are resident on commercial aircraft. These airborne weather radar systems currently supply real-time information about the position and intensity of weather conditions ahead of the aircraft generally along its current flight path. Assessing the weather condition requires both reflectivity information, which relates to rate of precipitation due to the weather condition, and height information, which describes the vertical extent of the weather condition. Typically, the radar antenna mounted on the nose of the aircraft scans through an azimuth angle, sweeping horizontally from side-to-side at a selected elevation, or vertical tilt, to detect weather conditions in an arc centered on the aircraft's flight path. The information about the position and intensity of weather conditions is displayed to the crew on a radar screen mounted in the cockpit.
Conventional weather radar systems provide a single elevation, i.e., vertical, plan view on the display screen. The plan view is a view looking down, with the radar antenna scanning through an azimuth angle at a particular elevation angle, the up-down tilt of the radar antenna. The tilt or elevation angle is manually controlled using a “tilt control.” The elevation angle or tilt of the display is adjusted to obtain an impression of the height of the various weather conditions and their physical relationship to the host aircraft. Use of conventional radar systems requires substantial training and experience to accurately analyze a potential weather threat based on this information. In airborne radar, user workload is an important consideration. Workload considerations are magnified during approach and landing under adverse weather conditions. U.S. Pat. No. 5,392,048 entitled, Weather Radar System Including An Automatic Step Scan Mode, issued to Michie on Feb. 21, 1995, the complete disclosure of which is incorporated herein by reference, discloses a weather radar system which is operable in an automatic mode that positions the antenna beam to scan an elevation axis in incremental steps between upper and lower scan limits while continuously scanning an azimuth axis.
Another weather radar system scans the radar antenna in a vertical, or elevation, mode to display on the radar screen a vertical side view at a given radial angle. Height versus range information at a selected azimuth angle is thereby readily available. The antenna is incrementally stepped through the limits of the azimuth angle. This design also requires skill and constant attention to assess weather conditions at all azimuth angles.
Still another weather radar system disclosed by U.S. Pat. No. 4,940,987, entitled Automatic Horizontal And Vertical Scanning Radar, issued to Frederick on Jul. 10, 1990, the complete disclosure of which is incorporated herein by reference, simultaneously displays two views of a weather condition: a conventional plan view, and a vertical side or frontal view. The net effect is a view of the weather condition in two intersecting planes. One plane is a horizontal plan view, while the other plane is user selected as either a vertical slice along the radar range axis, or a vertical slice perpendicular to the range axis. The display update rate for this weather radar system is slow because the antenna beam must be positioned to cover a full volume of space, and the system requires substantial computer storage or memory capacity to support the large amount of information needed. Workload is high because of the requirement to select range or radial angle for the vertical slices or views. Also the data is included in two intersecting planes and must be visually integrated and interpreted to be of value.
U.S. Pat. No. 5,198,819, entitled Weather Radar Display System, issued to Susnjara on Mar. 30, 1993, the complete disclosure of which is incorporated herein by reference, discloses a weather radar system that stores multiple plan views in separate display memories. The views are displayed in overlapping fashion on the screen, with only the highest of the stored views shown in true weather condition precipitation intensities. The storage of multiple plan views to fill multiple memory planes suffers a long lag time. Each horizontal scan usually takes several seconds to complete. Therefore, even if the currently scanned view is continuously updated, the displayed complete view includes data that may lag by almost a minute. This problem is especially significant during and immediately after changes in aircraft heading. Also, implementation of the disclosed weather radar system is difficult due to the complexity of the display unit required to show the overlapping plan views.
Although the path that weather conditions, or “storm cells,” take has not been highly predictable over very long periods, given the position and intensity history of a weather condition, short-term predictions of future location and intensity can be made effectively. Several incidents have occurred in which an aircraft encountered severe weather condition during a critical phase of flight, resulting in a serious threat to the safety of the aircraft, its crew and passengers.
Weather Tracking
Systems and methods providing for real-time weather tracking and storm movement prediction on a regional or global scale are well known. For example, U.S. Pat. No. 5,717,589, entitled System And Method Providing For Real-time Weather Tracking And Storm Movement Prediction, issued to Thompson et al on Feb. 10, 1998, the complete disclosure of which is incorporated herein by reference, discloses a real-time weather tracking system and method for tracking and predicting future movements of significant weather by integrating real-time weather data collected from many different sources, communicating the integrated data to remote users, and computing, predicting, and displaying the expected movements of significant weather. U.S. Pat. No. 5,717,589 also discloses a system and method for combining the integrated data with geographical information and displaying the combined real-time weather data and geographical information.
Cross-correlation methods are widely used in conventional real-time weather tracking and prediction systems employing weather radar images. For example, a publication by Yoshio Asuma, Katsuhiro Kikuchi, and Hisashi Kon, entitled A Method for Estimating the Advection Velocity of Radar Echoes Using a Simple Weather Radar System, Geophysical Bulletin of Hokkaido University, Vol. 44, October, 1984, pages 23-34, and another publication by Yoshio Asuma, Katsuhiro Kikuchi, and Hisashi Kon, entitled Experiments for a Very-Short-Range Prediction of Snowfall Using a Simple Weather Radar System, Geophysical Bulletin of Hokkaido University, Vol. 44, October, 1984, pages 35-51, the complete disclosures of which are incorporated herein by reference, each describe cross-correlation methods of weather tracking and prediction. Briefly, cross-correlation uses two weather radar images separated by an arbitrary time interval DELTA T. During shifting of one of the images, respective correlation values of the image gray levels are calculated. The amount of movement of the precipitation field between the two frames is the shift having the greatest correlation value. Using the calculated amount of movement, a parallel translation is performed on the precipitation field within the most current weather radar image. The resulting image is the forecast image.
FIGS. 1A and 1B illustrate that the radar echo within the weather radar image 10 has both large and small echo cells 12 as its fundamental elements, as described in U.S. Pat. No. 5,974,360 by Otsuka et al. One precipitation field 14 is formed when these echo cells 12 combine to form a group. Hereinafter, echo cells 12 are referred to simply as “echoes.” In a weather radar image 10, a precipitation field 14 possessing multiple different dynamics may exist. According to the cross-correlation methods of weather tracking and prediction the constant repetition of deformation and appearance and dissipation of echoes 12 in a weather condition is generalized as a precipitation field 14 moving along with the flow of the atmosphere. Conventional cross-correlation methods do not distinguish between the moving velocity of the individual echoes 12 indicated by respective arrows 16 and the moving velocity of the precipitation field 14 as a whole. Rather, the method calculates one or more global movement vectors 18 based on the correlation value of the gray level of a large portion of the precipitation field 14 from the radar images of the two frames.
FIG. 2 illustrates the method of obtaining the cross-correlation coefficient from the two weather radar images R1, R2, which are measured at two different times separated by a time interval DELTA T. In FIG. 2, the gray levels of the image or the lattice point (ij) in the radar images are assigned as R1(ij) and R2(ij), respectively, for the two measured images R1, R2. The fields to be correlated are A and B, respectively. The shift of the two radar images when calculating the correlation value is assigned as (k, l). In FIG. 2, the oblique lines 22, 24 indicate the field to be correlated, while the arrow 26 in the center indicates the direction of the movement of the echo pattern. The cross-correlation coefficient SIGMA σk,l is obtained from the two weather radar images R1, R2, according to:
                              σ                      k            ,            l                          =                                                            ∑                                  i                  =                  1                                A                            ⁢                                                ∑                                      j                    =                    1                                    B                                ⁢                                                                            R                      1                                        ⁡                                          (                                              i                        ,                        j                                            )                                                        ⁢                                                            R                      2                                        ⁡                                          (                                                                        i                          +                          k                                                ,                                                  j                          +                          l                                                                    )                                                                                            -                          A              ⁢                                                          ⁢              B              ⁢                                                          ⁢                                                R                  _                                1                            ⁢                                                R                  _                                2                                                                                        (                                                                            ∑                                              i                        -                        1                                            A                                        ⁢                                                                                  ⁢                                                                  ∑                                                  j                          -                          1                                                B                                            ⁢                                                                                                    R                            1                                                    ⁡                                                      (                                                          i                              ,                              j                                                        )                                                                          2                                                                              -                                      A                    ⁢                                                                                  ⁢                    B                    ⁢                                                                                  ⁢                                                                  R                        _                                            1                      2                                                                      )                            ⁢                                                          ⁢                              (                                                                            ∑                                              i                        -                        1                                            A                                        ⁢                                                                                  ⁢                                                                  ∑                                                  j                          -                          1                                                B                                            ⁢                                                                                                    R                            2                                                    ⁡                                                      (                                                          i                              ,                              j                                                        )                                                                          2                                                                              -                                      A                    ⁢                                                                                  ⁢                    B                    ⁢                                                                                  ⁢                                                                  R                        _                                            2                      2                                                                      )                                                                        (                  Eq          .                                          ⁢          1                )                                                      where            ⁢                          :                        ⁢                                                  ⁢                                          R                _                            1                                =                                                    ∑                                  i                  =                  1                                A                            ⁢                                                ∑                                      j                    =                    1                                    B                                ⁢                                                      R                    1                                    ⁡                                      (                                          i                      ,                      j                                        )                                                                                      A              ⁢                                                          ⁢              B                                      ;        and                            (                  Eq          .                                          ⁢          2                )                                          where          ⁢                      :                    ⁢                                          ⁢                                    R              _                        2                          =                                                            ∑                                  i                  =                  1                                A                            ⁢                                                ∑                                      j                    =                    1                                    B                                ⁢                                                      R                    2                                    ⁡                                      (                                                                  i                        +                        k                                            ,                                              j                        +                        l                                                              )                                                                                      A              ⁢                                                          ⁢              B                                .                                    (                  Eq          .                                          ⁢          3                )            
FIG. 3 is an exemplary illustration of one possible value of a cross-correlation coefficient σk, l obtained through calculation using the above equations.
FIG. 4 illustrates an interpolation based on a second order function performed on the cross-correlation σK,L at point (K,L) of the lattice point where the greatest cross-correlation value exists, and the four cross-correlation values in its vicinity: σ−x, σ+x, σ−y, and σ+y. FIG. 4 also illustrates the X component of the shift (k1, l1) between the lattice point where the greatest cross-correlation value exists and the point where the cross-correlation value resulting from the compensation is greatest, which is not necessarily a lattice point. The maximum cross-correlation value resulting from the compensation (for the x component of the shift only) is obtained according to:
                              k          1                =                                            σ                              -                x                                      -                          σ                              +                x                                                          2            ⁢                          (                                                σ                                      -                    x                                                  -                                  2                  ⁢                                      σ                                          K                      ,                      L                                                                      +                                  σ                                      +                    x                                                              )                                                          (                  Eq          .                                          ⁢          4                )                                          l          1                =                                            σ                              -                y                                      -                          σ                              +                y                                                          2            ⁢                          (                                                σ                                      -                    y                                                  -                                  2                  ⁢                                      σ                                          K                      ,                      L                                                                      +                                  σ                                      +                    y                                                              )                                                          (                  Eq          .                                          ⁢          5                )            
Accordingly, the cross-correlation value is greatest when the two weather radar images R1, R2 are shifted by (K+k1, L+l1). Using this information, the movement vector V describing the direction and the speed of the global movement 18 of the echo pattern forming the precipitation field 14 is obtained according to:Vx=(K+k1)Δx/Δt and  (Eq. 6)Vy=(L+l1)Δy/Δt  (Eq. 7)where: Vx and Vy, respectively, indicate the x component and the y component of the movement, and                Δt is the elapsed time between consecutive measurements.        
A radar image of a time after the measured time is predicted by extrapolating the echo pattern within a weather radar image measured at a certain time by employing the movement vector obtained through the equations (6), (7), above.
A forecast image J (i,j) of a time DELTA T after the measured time of the most current weather radar image I (i,j) is obtained from the calculated movement vector using the weather radar image I (i,j) as the input image and employing Vx and Vy. The forecast image J(i,j) is defined as an image resulting from a parallel translation of the input image I (i,j) based on the amount of movement in the horizontal direction Sx and the amount of movement in the vertical direction Sy, where:Sx=DELTA T·Vx and  (Eq. 8)Sy=DELTA T·Vy  (Eq. 9)
However, the amount of movement is not restricted to integer values. If the non-integer shift from the lattice point of the moved image is expressed by:δx=Sx└Sx┘ and  (Eq. 10)δy=Sy└Sy┘,  (Eq. 11)where: └Nx┘ is the largest integer that does not exceed N, then the forecast image J (i,j) is defined as:
                                                                        J                ⁡                                  (                                      i                    ,                    j                                    )                                            =                            ⁢                                                                    (                                          1                      -                                              δ                        x                                                              )                                    ⁢                                      (                                          1                      -                                              δ                        y                                                              )                                    ⁢                                      I                    ⁡                                          (                                                                        i                          -                                                      ⌊                                                          S                              x                                                        ⌋                                                                          ,                                                  j                          -                                                      ⌊                                                          S                              y                                                        ⌋                                                                                              )                                                                      +                                                                                                      ⁢                                                                    (                                          1                      -                                              δ                        x                                                              )                                    ⁢                                      δ                    y                                    ⁢                  I                  ⁢                                      (                                                                  i                        -                                                  ⌊                                                      S                            x                                                    ⌋                                                                    ,                                              j                        -                                                  ⌊                                                      S                            y                                                    ⌋                                                +                        1                                                              )                                                  +                                                                                                      ⁢                                                                                          δ                      x                                        ⁡                                          (                                              1                        -                                                  δ                          y                                                                    )                                                        ⁢                                      I                    ⁡                                          (                                                                        i                          -                                                      ⌊                                                          S                              x                                                        ⌋                                                    +                          1                                                ,                                                  j                          -                                                      ⌊                                                          S                              y                                                        ⌋                                                                                              )                                                                      +                                                                                                      ⁢                                                δ                  x                                ⁢                                  δ                  y                                ⁢                                                      I                    ⁡                                          (                                                                        i                          -                                                      ⌊                                                          S                              x                                                        ⌋                                                    +                          1                                                ,                                                  j                          -                                                      ⌊                                                          S                              y                                                        ⌋                                                    +                          1                                                                    )                                                        .                                                                                        (                  Eq          .                                          ⁢          12                )            The lattice points of the forecast image J which have no correspondence to that of the input image, that is, the blank space of the forecast image resulting from the parallel translation, are set to have the value of zero.
The forecast image is obtained in the same manner for cases other than whereVx>0 and Vy>O.
FIG. 5A describes a situation in which the global movement 18 of the precipitation field 14 formed by the group of echoes 12 may be extremely slow when compared to the movement velocity of the individual echoes 12. This difference between the global movement 18 of the precipitation field 14 and the movement velocity of the individual echoes 12 is the result of the individual echoes 12 having differing movement velocities due to the above mentioned constant repetition of deformation and appearance and dissipation of individual echoes 12. In the case where precipitation field 14 possesses such multiple different movements, each of the different movements may define different local precipitation fields 14′ through 14N. Although different local precipitation fields 14′ through 14N may have significantly different velocities 28, the forecast image obtained using a cross-correlation method is still reasonably accurate when the prediction lead time is short because there is a tendency for a uniform parallel translation due to the small amount of appearances, dissipations, and deformations of the echoes 12 during the short forecast interval.
However, during longer forecast intervals, each of the different local precipitation fields 14′ through 14N defined by the different movements may be treated separately, thereby increasing the accuracy of the forecast. U.S. Pat. No. 5,974,360, entitled, Method And Equipment For Weather Image Prediction, issued to Otsuka et al on Oct. 26, 1999, the complete disclosure of which is incorporated herein by reference, discloses another system and method for the real-time tracking and predicting local, short-term weather conditions using multiple weather radar images, wherein each of the different local precipitation fields 14′ through 14N are treated separately. Briefly, as illustrated in FIG. 5B, the U.S. Pat. No. 5,974,360 patent discloses breaking precipitation field 14 down into multiple smaller segments 30. Velocity fields 32 of the echoes local to individual segments 30 are computed, and from within the image is extracted a single precipitation field 14′ formed of multiple segments 30 possessing similar velocity fields 32 with respect to time and space. The method extrapolates multiple precipitation fields 14′ through 14N over a forecast period and generates a forecast radar image J (i,j) by synthesizing the resulting image.
Flight Management Systems
Flight Management Systems (FMS) in various configurations (not shown) are known in the art as an information integration and flight control tool for commercial aircraft, as defined by the ARINC characteristic 702, the complete description of which is incorporated herein by reference. The FMS is an extension of the area navigation (RNAV) capability originally certified for aircraft in 1971. It performs the basic RNAV functions of waypoint navigation and coupled guidance as well as tuning of the aircraft's VOR/DME receivers (Variable Omnidirectional Range/Distance Measuring Equipment), the automatic selection of VORTAC (collocated VOR and DME facilities) stations, and the mixing of inertial, radio, heading and air data sensor inputs to provide optimal navigation accuracy and automatic control of engine parameters for all phases of flight. The FMS typically includes a computer with a memory module coupled thereto, a control and display unit (CDU), and a map display. The CDU provides a flight crew interface with the FMS, and the FMS informs the crew of the aforementioned flight data for any given flight condition. The pilot uses the CDU to input vertical and lateral flight control mode selections that supercede preexisting and/or default flight control modes. The vertical mode is used to control the aircraft's speed, by controlling engine thrust and aircraft attitude, and aircraft altitude between takeoff and landing.
Typically, a pilot selects the thrust rating of the engines and a desired vertical speed for the initial climb after takeoff. The pilot then typically sets thrust at the rating level of the engines and speed at a desired climb speed for the en route climb to cruise altitude. When cruise altitude is reached, speed is set based on an established criterion, such as most economical, shortest elapsed time, or another criterion consistent with maintaining the cruise altitude. During descent the pilot typically sets the engines to their idle thrust rating and selects a descent speed designed to achieve a desired descent profile. The lateral mode is used to select any one of various options, such as selection of a particular heading to change the aircraft's flight path to the selected heading. Another option allows the present heading to be maintained by a heading hold selection. Automatic navigation may also be selected to track a preprogrammed route using steering signals from an inertial or area navigation system.
Various FMS devices have been enhanced by addition of more sophisticated automatic flight control modes of operation. These include flight level change (FLCH), vertical navigation (VNAV), and lateral navigation (LNAV) flight control modes of operation. The FLCH mode automatically manages thrust and speed to climb or descend from one altitude to another. The VNAV mode provides automatic optimized profile control from initial climb through final approach, including adherence to terminal area procedure speed and altitude constraints. The LNAV mode provides automatic steering to a preprogrammed route including selected terminal automatic flight control area procedures.
One U.S. Pat. No. 5,739,770, entitled Off-Path Descent Guidance By A Flight Management System, issued to Liden on Apr. 14, 1998, the complete disclosure of which is incorporated herein by reference, discloses a method for providing off-path guidance during a descent. Another U.S. Pat. No. 4,811,230, entitled Intervention Flight Management System, issued to Graham, et al on Mar. 7, 1989, the complete disclosure of which is incorporated herein by reference, discloses an Intervention Flight Management System (IFMS) that allows a pilot to intervene in the operation of a preprogrammed flight management computer and change the speed and/or flight path of an aircraft in response to air traffic control (ATC) instructions using lateral and vertical control subroutines that override the preprogrammed instructions controlling the flight management computer, thereby reducing pilot workload when pilot attention should be focused on flight progress.
A principal objective of a FMS is to minimize the cost of flight. FMS are known in the art that utilize an adjustable cost index in providing a minimum-cost flight profile. Some known FMS achieve this objective by generating vertical and lateral profiles that minimize direct operating cost (DOC), where direct operating cost is the cost of fuel plus other costs that are proportional to flight time. Flight time costs, such as crew costs, maintenance, repair and replacement of equipment, that may be prorated with flight time, is represented in the FMS by a cost index. The FMS provides a speed command as a function of the cost index at every point in the flight profile that minimizes DOC. One FMS disclosed by U.S. Pat. No. 4,760,530, entitled, Flight Management System Providing Minimum Total Cost, issued to Liden on Jul. 26, 1988, the complete disclosure of which is incorporated herein by reference, utilizes an adjustable cost index in providing a minimum-cost flight profile.
Another objective of a FMS is to determine the speed necessary to arrive at destination at a particular ETA (estimated time of arrival) and generate a signal to control the aircraft's speed to achieve the desired ETA. U.S. Pat. No. 4,774,670, entitled Flight Management System, issued to Palmieri on Sep. 27, 1988, the complete disclosure of which is incorporated herein by reference, discloses an improvement to a FMS for accepting flight data information, including a required ETA, and generating therefrom an airspeed control signal modifying the actual airspeed of the aircraft to correspond to a required airspeed. The airspeed control signal is a function of the flight data information, including the actual airspeed, flight plan data, and wind data. The output signal is coupled to the aircraft's autothrottle to modify the output thereof to attain and to maintain the required airspeed.
Another U.S. Pat. No. 5,051,910, entitled Wind Forecast Error Compensation For 4-D Guidance In A Aircraft Flight Management System, issued to Liden on Sep. 24, 1991, the complete disclosure of which is incorporated herein by reference, discloses a FMS generating an aircraft speed control for achieving a desired arrival time. The FMS disclosed in the U.S. Pat. No. 5,051,910 patent generates a speed adjustment coefficient for calculating a wind forecast error, and generates a signal for adjusting the command speed outputted from the speed generator. The speed adjusting signal utilizes the calculated wind forecast error, actual wind speed at the current aircraft position, and wind forecast error at the aircraft position to compensate for error in the wind forecast so that the desired arrival time is achieved.
Regardless of the sophistication of the modes of operation, in all flight management systems, the pilot chooses the available modes that will best accomplish the desired vertical flight profile and lateral routing. In most instances, the pilot plans the flight in advance, both laterally and vertically, and preprograms the LNAV and VNAV modes so that the desired flight path will be followed, thereby reducing workload when pilot attention should be focused on flight progress.
One of the many functions of a FMS is to use a simulation algorithm to construct a sequence of waypoints and connecting line segments that is referred to as a “flight plan” shown in FIGS. 6A and 6B. FIG. 6A illustrates a horizontal view 40 of the flight plan. In operation, the pilot, after takeoff, selects the route to be flown and establishes a flight plan, which the pilot then inputs into the FMS via the CDU. The FMS constructs a flight path 42 from the aircraft position to the destination, which is then used as a reference for lateral and vertical guidance. The lateral component of the path is defined by waypoints 44 and various types of line segments 46 connecting the waypoints 44. The flight plan begins at the origin runway threshold (not shown) and ends at the end of descent point E/D. 14. The FMS is coupled to the aircraft's autothrottle (not shown) and autopilot (not shown) for effecting airspeed changes.
FIG. 6B illustrates the vertical component 48 of the flight plan, which is composed of three principal phases of flight: climb, cruise and descent. As part of the performance function of a FMS, a descent path is constructed from a T/D (top of descent) point at the final cruise altitude, to a defined E/D (end of descent) point with a prescribed altitude constraint. The E/D point may, for example, be the destination runway threshold, 50 feet above the runway, or it may be some other earlier waypoint, such as the FAF (final approach fix). The E/D point is selected as part of the flight planning function of the FMS. The descent path is then constructed so that the aircraft will arrive at the E/D point using selected speed and thrust profiles in the descent phase, and so that prescribed speed and altitude constraints at various descent points are satisfied.
The FMS simulation algorithm typically develops the flight path 42 using prescribed speed and altitude constraints at selected waypoints 44, a policy speed profile, wind and temperature forecast data, track direction relative to the wind direction, aircraft gross weight at each point, guidance laws such as the turn radius in a turn, and aerodynamic characteristics of the aircraft, such as thrust, drag, fuel-flow, speed envelope, and other aircraft characteristics as required for flight simulation.
During every phase of flight, and particularly during takeoff and landing, an aircraft can encounter hazardous flight conditions caused by intense weather conditions, hereinafter referred to as “storm cells.” For example, thunderstorms and rain showers often give rise to microbursts, which are intense localized downdrafts that spread along the ground, producing the dangerous phenomena known as windshear. Thus, the safety and comfort of flight would be improved if the weather data collected by an aircraft weather radar was used to project a short time into the future the position and intensity of such storm cells relative to the aircraft and a radar display was used to relate the information to the crew.
However, although radar systems are known for detecting weather conditions along the flight path of an aircraft and other methods are known for short-term prediction of weather condition movements, no method is known for using an aircraft weather radar to detect and record the position, direction and intensity of a weather condition for a limited period and to use the track and intensity information to forecast a position and intensity of the weather condition at a time in the near future. Nor is an aircraft weather radar known that operates such a weather condition position and intensity forecasting method and displays the forecast to the aircraft crew.
Furthermore, the safety and comfort of flight would be further improved if the projected future weather information was used to determine whether a coincidence with a storm cell will occur and result in a threat to the safety of flight.
Also, although FMS (Flight Management Systems) are known for determining the intended flight path of an aircraft, no method is known for combining the FMS information, such as speed, flight path, and phase of flight information, with a position and intensity weather condition forecast to determine whether an aircraft will intercept an unsafe weather condition. Nor is a method known for generating a suitable alert or warning to the aircraft crew when such an interception of an unsafe weather condition is determined.
Thus, although real-time weather tracking on a regional or global scale is known, what is needed is a weather radar system for use on aircraft that provides information on the intensity and short-term movement of weather conditions in close proximity to the host aircraft. Also desirable is a method and apparatus combining the near-term weather forecast with typical FMS information to determine when an aircraft will intercept an unsafe weather condition and provide an alert or warning to the crew when such an interception is predicted that may threaten the safety of flight.